Early Identification and Prognosis Prediction of Sepsis Through Multiomics
EIPPSM
1 other identifier
observational
900
1 country
1
Brief Summary
This study aims to integrate multi-omics data and clinical indicators to reveal pathogen-specific molecular patterns in patients with sepsis and establish prognostic prediction models through multiple machine learning algorithms.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Jan 2022
Longer than P75 for all trials
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
Click on a node to explore related trials.
Study Timeline
Key milestones and dates
Study Start
First participant enrolled
January 1, 2022
CompletedFirst Submitted
Initial submission to the registry
March 22, 2022
CompletedFirst Posted
Study publicly available on registry
March 31, 2022
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 31, 2024
CompletedStudy Completion
Last participant's last visit for all outcomes
December 31, 2025
CompletedJanuary 24, 2024
January 1, 2024
3 years
March 22, 2022
January 22, 2024
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Pathogen-specific patterns
To elucidate the unique infection pathogen-specific molecular patterns in septic patients
March 2022 - December 2023
Secondary Outcomes (1)
Prognostic prediction models
March 2022 - December 2024
Study Arms (5)
GN
Gram-negative bacteria infection group
GP
Gram-positive bacteria infection group
Fungal
Fungal infection group
Viral
Viral infection group
Control
Non-sepsis group
Eligibility Criteria
The study cases are from the Department of Critical Care Medicine, a top-grade hospital in Yantai
You may qualify if:
- Patients with sepsis or septic shock who meet the diagnostic criteria (2016 sepsis 3.0 standard);
- Age 18～85 years old.
You may not qualify if:
- ICU stay of the subjects less than 72 hours;
- Female subjects who are pregnant;
- The subjects not sure if infected;
- The subjects performed CPR;
- The subjects suffer from chronic renal disease;
- The subjects with incomplete clinical data.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Yantai Yuhuangding Hospital
Yantai, Shandong, 264000, China
Related Publications (1)
Wang J, Sun Y, Teng S, Li K. Prediction of sepsis mortality using metabolite biomarkers in the blood: a meta-analysis of death-related pathways and prospective validation. BMC Med. 2020 Apr 15;18(1):83. doi: 10.1186/s12916-020-01546-5.
PMID: 32290837RESULT
Biospecimen
Urine, and plasma
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Jing Wang
Yantai Yuhuangding Hospital
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
March 22, 2022
First Posted
March 31, 2022
Study Start
January 1, 2022
Primary Completion
December 31, 2024
Study Completion
December 31, 2025
Last Updated
January 24, 2024
Record last verified: 2024-01
Data Sharing
- IPD Sharing
- Will not share